Interpretable Math Problem Solving. Due to the intrinsic requirements of symbolic understanding and logical reasoning, interpretability of solvers plays an essential role in geometry problem solving. While the interpretability of geometry problem solvers is rarely explored, some pioneering work has been proposed in the general math problem solving domain. Broadly there are two main lines of achieving interpretable solving steps for math problems. The first generates intermediate structural results of equation templates [1]}, [2]}, operational programs [3]} and expression trees [4]}, [5]}, [6]}. The second line of work with a higher level of interpretability translates the math problems into symbolic language and conducts logical reasoning iteratively to predict the final results [7]}, [8]}. Furthermore, inspired by work on semantic parsing [9]}, [10]}, [11]}, we claim structured diagram parsing and joint semantic representations for text and diagrams is critical in interpretable geometry problem solving.
